10 research outputs found

    OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

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    Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

    Archaeal genetics – the third way

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    For decades, archaea were misclassified as bacteria on account of their prokaryotic morphology. Molecular phylogeny eventually revealed that archaea, like bacteria and eukaryotes, are a fundamentally distinct domain of life. Genome analyses have confirmed that archaea share many features with eukaryotes, particularly in information processing, and therefore can serve as streamlined models for understanding eukaryotic biology. Biochemists and structural biologists have embraced the study of archaea but geneticists have been more wary, despite the fact that genetic techniques for archaea are quite sophisticated. It is high time for geneticists to start asking fundamental questions about our distant relatives
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